# Realization of Stochastic Neural Networks and Its Potential Applications

arXiv: https://arxiv.org/abs/2011.06427 · HTML: https://mlsanity.com/paper/2011.06427/

## Key facts

- Cited by 1 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 12 Nov 2020.

## Built on by (most cited first, 1 of 1)

- [Coin Flipping Neural Networks](https://mlsanity.com/paper/2206.09182/) (2022)

## Abstract (arXiv)

Successive Cancellation Decoders have come a long way since the implementation of traditional SC decoders, but there still is a potential for improvement. The main struggle over the years was to find an optimal algorithm to implement them. Most of the proposed algorithms are not practical enough to be implemented in real-life. In this research, we aim to introduce the Efficiency of stochastic neural networks as an SC decoder and Find the possible ways of improving its performance and practicality. In this paper, after a brief introduction to stochastic neurons and SNNs, we introduce methods to realize Stochastic NNs on both deterministic and stochastic platforms.